Predicting aggression in children with ADHD

The present study uses structural equation modeling of latent traits to examine the extent to which family factors, cognitive factors and perceptions of rejection in mother-child relations differentially correlate with aggression at home and at school.

R E S E A R C H Open Access

Predicting aggression in children with ADHD

Elif Ercan1, Eyüp Sabri Ercan2*, Hakan At ılgan3

, Bürge Kabukçu Ba şay2

, Taciser Uysal2, Sevim Berrin İnci4

and Ülkü Akyol Ard ıç5

Abstract

Objective: The present study uses structural equation modeling of latent traits to examine the extent to which family factors, cognitive factors and perceptions of rejection in mother-child relations differentially correlate with aggression at home and at school

Methods: Data were collected from 476 school-age (7–15 years old) children with a diagnosis of ADHD who had previously shown different types of aggressive behavior, as well as from their parents and teachers Structural

equation modeling was used to examine the differential relationships between maternal rejection, family, cognitive factors and aggression in home and school settings

Results: Family factors influenced aggression reported at home (.68) and at school (.44); maternal rejection seems

to be related to aggression at home (.21) Cognitive factors influenced aggression reported at school (.-05) and at home (−.12)

Conclusions: Both genetic and environmental factors contribute to the development of aggressive behavior in ADHD Identifying key risk factors will advance the development of appropriate clinical interventions and

prevention strategies and will provide information to guide the targeting of resources to those children at highest risk

Keywords: Aggression, ADHD, Structural equation modeling

Background

ADHD is one of the most prevalent childhood disorders,

and it is a community health problem that may result in

significant psychiatric, social and academic problems if

not treated ADHD frequently co-occurs with other

psy-chiatric disorders [1,2] Research shows that aggression

is an important associated feature of ADHD, and it is

essential in understanding the impact of the disorder

and its treatment [3] The presence of comorbid

aggres-sion in ADHD does not appear to be spurious, and the

severity and/or presence of aggression and ADHD may

significantly impact its long-term prognosis The etiology

of aggression in ADHD is not clearly understood

How-ever, aggression can be considered to be an outcome

of the interaction between genetic and environmental

factors [4] Aggression is thought to be inherited, and

the concordance of maternal twins is between 28 and

.72 [5] Compared to children who only have ADHD, it

is more likely that children with ADHD and ODD or

CD have fathers with an Antisocial Personality Disorder Pfiffner et al [6] found that children who have fathers with Antisocial Personality Disorder are more at risk for developing behavioral problems

The most significant family factors influencing the oc-currence of aggression in ADHD are as follows: large family size, the attitude of the family towards aggression, disciplinary or negative parenting, low socio economic status and family conflict [7] Extended family and low socio economic status may cause aggression as a result

of inadequate attention

Parental attitudes are particularly important in psy-chiatric disorders, including aggression and ADHD [8] However, there is a gap in the literature regarding the nature of the relationship between negative parental at-titudes and psychiatric disorders that influence child-hood aggression The debate over whether aggression in children caused by parents’ lack of interest and/or their hostile and critical attitudes towards their children, or

* Correspondence: eyercan@hotmail.com

2

Department of Child and Adolescent Psychiatry, Ege University Faculty of

Medicine, Izmir, Turkey

Full list of author information is available at the end of the article

© 2014 Ercan et al.; licensee BioMed Central Ltd This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article,

whether negative parenting is instead caused by

chil-dren’s behavioral problems remains unresolved [9]

Cognitive deficits primarily in the verbal area play a role

in the etiology of aggression Previous data regarding the

interaction between cognition and aggression reveal such

general cognitive predictors of aggression as lower

in-telligence quotients, reading difficulties, and problems

associated with attention and hyperactivity [10] Many

studies suggest that aggressive children experience

prob-lems in social cognitive areas [11,12] and have lower IQ

scores [13,14] In a meta-analysis of twenty-seven studies,

seventeen studies reported negative associations between

cognitive functions and disruptive behaviors [15]

Some of the most comprehensive research examining

the relationship between ADHD and aggression using

ad-vanced statistical analyses has been conducted by Miller

et al [16] In that study, 165 children with ADHD and

dis-ruptive behaviors between the ages of 7 and 11 were tested

using structural equation modeling (SEM) to determine

the influence of family and cognitive factors on aggression

One of the most important characteristics of the study is

that it attempts to explain aggression in children with

ADHD with information from two sources: parents and

teachers Family factors including present and past

aggres-sion by parents and the number of siblings are examined

Cognitive factors, verbal IQ, reading and mathematical

achievement are also examined The study found that

family factors are related to aggression at home and at

school, whereas cognitive factors are only related to

ag-gression at school

The purpose of our study is to evaluate the influence

of family, parent–child relations and cognitive factors on

the development of aggression in children within a

lar-ger and a non-western sample We use structural

equa-tion modeling and include informaequa-tion from the parents,

teachers and the child as the information source This

method is ideal, as it is important to receive information

from multiple sources to explain a multicomponent

con-cept such as aggression Accordingly, we include

evalua-tions of the mothers’ acceptance or rejection of the child

with ADHD in the structural equation model in addition

to information received from parents and teachers To

our knowledge, this is the first study to consider

infor-mation from the parent, teacher and the child regarding

aggression in ADHD In addition, we examine

mother-child relationships in detail regarding the etiology of

ag-gression [8,16], as we consider it crucial to include the

perception of acceptance or rejection of children with

ADHD by their mothers as a possible latent factor

In our study, past and current aggression by the parents,

the number of people living in the home and the number

of siblings were used as family factors To define cognitive

factors in the present study, verbal and performance IQ

and school success variables are used To evaluate the

perceptions of children regarding their mothers’ accep-tance or rejection, warmth, aggression and rejection va-riables specified in the theory of parental acceptance and rejection are used [17]

Methods Diagnosis of ADHD

In total, 476 subjects referred to the Disruptive Behavior Disorders Clinic in 2011 with a diagnosis of ADHD with aggressive behaviors were included in the study, in ad-dition to their parents and teachers Approval from The Institutional Review Board (IRB) at the Ege University School of Medicine was attained before the study began, and informed consent was gathered from the parents Our recruitment and screening procedures were designed

to collect data from a carefully diagnosed sample of children for ADHD comorbidities and subtypes The children were first interviewed by a senior child psychiatry resident using the Schedule for Affective Disorders and Schizophrenia for School Age Children: Present and Lifetime version (K-SADS-PL) [18] The K-SADS-PL is a highly reliable semi-structured interview for the assessment of a wide range of psychiatric disorders Cognitive assessments were performed using the Wechsler Intelligence Scale for Children-Revised (WISC-R) [19] Subjects with an IQ less than 70 were excluded from the study Those who met the inclusion criteria for the study also completed the Children’s Aggression Scale-Parent and Teacher Versions (CAS-P, CAS-T), Teacher Report Form (TRF), Turgay DSM-IV Disruptive Behavior Disorders Rating Scale (T-DSM-IV-S) parent and teacher forms, and the Parental Acceptance and Rejection Questionnaire (PARQ), com-pleted by both the parents and teachers of the participants The returned parent and teacher version of T-DSM-IV-S forms were scored, and the children who scored less than one standard deviation below the relevant age norms on the Attention Deficiency and Hyperactivity Disorder subscales were excluded from the study The T-DSM-IV-S was developed by Turgay [20] and trans-lated and adapted by Ercan, Amado, Somer, & Cikoglu [21] The T-DSM-IV-S is based on DSM-IV diagnostic criteria and assesses hyperactivity-impulsivity (9 items), inattention (9 items), opposition-defiance (8 items), and conduct disorder (15 items) Symptoms are scored by assigning a severity estimate for each symptom on a 4-point Likert scale (0 = not at all; 1 = just a little; 2 = quite

a bit; and 3 = very much) The subscale scores on the T-DSM-IV-S were calculated by summing the scores on the items of each subscale Similar scales derived from the DSM-IV diagnostic criteria for AD/HD, such as the AD/HD Rating Scale IV, have been shown to have ad-equate criterion-related validity and good reliability in different cultures both by parents and teachers [22,23] The second diagnostic interview was conducted by an

experienced child psychiatrist who knew that the child

was a candidate for the study but was blind to the first

judge’s diagnosis of comorbid disorders and ADHD

sub-types.“A best estimate procedure” was used to determine

the final diagnoses “Best estimate procedure” is defined

here as determining the diagnostic status after reviewing

all teacher and parent scales and the K-SADS-PL, and

WISC-R results

Dependent variables of the study

This study has two main dependent measures:

aggres-sion at home and aggresaggres-sion at school in elementary

school students with ADHD

Children’s aggression scale – parent & teacher forms

(CAS-P & CAS-T)

These scales were designed by Halperin et al [24,25]

Both the 33-item CAS–P and 23-item CAS–T require

informants to indicate the frequency (i.e., never, once

per month or less, once per week or less, 2–3 times per

week, or most days) with which the child has engaged in

various aggressive behaviors during the past year The

CAS–P was entered into the model to indicate

aggres-sion in the home, and the CAS–T was entered to

in-dicate aggression in school settings Each test has five

separate subscales: verbal aggression, aggression against

objects and animals, provoked physical aggression,

ini-tiated physical aggression, and the use of weapons

Independent variables of the study

This study includes three independent measures of

fa-milial risk factors, cognitive risk factors, and children’s

perceptions of acceptance and rejection in their

relation-ships with their mothers

Familial risk factors were evaluated by interview A

child psychiatrist asked the parents about the number of

siblings, the number of people living in the home, and

the parents’ present and past history of aggression

The Teacher Report Form (TRF) was used to obtain the

children’s academic performance, and the Wechsler

Intelligence Scale for Children-Revised (WISC-R) was

used to assess cognitive risk factors The “Parental

Acceptance/Rejection Questionnaire (PARQ)” was used

to determine the children’s perceptions of their

accep-tance/rejection by their mothers

The Parental Acceptance/Rejection Questionnaire (PARQ)

This scale was designed by Rohner, Saavedra and

Granum in 1978 to assess the perceived

acceptance/re-jection of children with respect to their relationships

with their parents The PARQ includes four sub-scales:

“Warmth (20 items), Hostility/Aggression (15 items),

Neglect and Indifference (15 items), and

Undifferen-tiated Rejection (10 items)” The total scores for these

sub-scales reflect the degree of perception, with higher scores indicating perceived rejection

Teacher Report Form (TRF)

The Teacher Report Form (TRF) was developed by Achenbach and Edelbrock [26] and adapted by Erol, Arslan, & Akçakın [27] The Turkish Form of the TRF is normed for children 4–18 years of age and provides reliable and valid measures of the children’s school adap-tation and problematic behaviors

Statistical methodology

In the first part of the data analysis, we used IBM PASW Statistics 18 for descriptive statistical analyses, and the data were presented as means (standard deviations), per-centages, medians, and minimum and maximum values, where appropriate In the second part, we used SPSS AMOS 18 for testing the structural equation model Results

In total, 476 subjects between 7 and 15 years of age (±2.11) diagnosed with ADHD were included in the study The majority (79% of participants; n = 376) were boys, and 21% (n = 100) were girls The distribution of diagnostic groups and their percentages in the study population are presented in Table 1 The cases were diagnosed as“pure” ADHD (37.8%), ADHD + ODD (44.3%) and ADHD + CD (17.9%) Descriptive statistics for the observed variables in the SEM hypothesis are presented in Table 2

SEM analysis of our proposed model consisted of two separate elements, of which the first is a measurement model (confirmatory factor analysis-CFA) and the second

is a structural model (Figure 1)

Measurement model (confirmatory factor analysis)

The measurement model based upon a confirmatory factor analysis indicated that each of our measures was related to the latent variables with determination coeffi-cients ranging from 92 to 01 Standardized and unstan-dardized regression weights, determination coefficients, and significance levels of these variables are shown in Table 3

Table 1 Diagnoses of participants and their percentages

in the study population (N = 476)

ADHD: Attention Deficit Hyperactivity Disorder, ADHD + ODD: Attention Deficit Hyperactivity Disorder and Oppositional Defiant Disorder, ADHD + CD: Attention Deficit Hyperactivity Disorder and Conduct Disorder.

Categorical variables

The dichotomous variables of our data were fathers’ or

mothers’ presence of aggression whether at present or

at past Until recently, two primary approaches to the

analysis of categorical data [28,29] have dominated this

area of research Both methodologies use standard

estimates of polychoric and polyserial correlations,

fol-lowed by a type of asymptotic distribution-free (ADF)

methodology for the structured model However,

because of the ultra-restrictive assumptions of these

methodologies, they are impractical and difficult to

meet

AMOS software uses Bayesian estimation (BE)

me-thod for categorical data via an algorithm termed the

Markov Chain Monte Carlo (MCMC) algorithm

Our data isn’t normally distributed so to estimate the

parameters, the model is put in a Bayesian framework

After BE procedure we treated our categorical variables

with a maximum likelihood (ML) procedure The BE

and ML procedures showed similar results with minimal

or no differences The comparisons of BE and ML

re-sults are shown in Table 4

Structural model

In the second part of SEM analysis, we calculated esti-mates of the relationships, and we tested our model for fit The structural model analysis in our study revealed statis-tically significant cross-loadings of aggression at home and aggression at school with the perception of accep-tance/rejection by the mothers, family factors, and cogni-tive factors (Figure 2) There was a non-significant loading

of the Perception of Acceptance or Rejection in Parent Relationships on aggression at school The standardized and unstandardized regression weights and the signifi-cance levels of these variables are shown in Table 3

Testing the model-fit

The χ2

value of our model was 249.199, which is a large value The Likelihood Ratio Test of the null hypothesis (H0) of thisχ2

value revealed a non-significant probability,

p = 11 As the χ2

probability of 11 was non-significant (p > 05), our model fit the data well

The χ2 value of our model was 249.199, which is a large value Because the χ2 statistic equals (N–1) Fmin, which means sample size minus 1, multiplied by the

Table 2 Descriptive statistics of observed variables in the SEM hypothesis (N = 476)

minimum fit function, this value tends to be substantial

when the model does not hold and when sample size is

large [30] When our sample size, which is large enough,

is considered, a higher χ2 value does make sense The

Likelihood Ratio Test results of the null hypothesis (H0)

of this χ2 value revealed a non-significant probability,

p = 0.11 The probability value associated with χ2

repre-sents the likelihood of obtaining aχ2 value that exceeds

theχ2 value when H0is true Thus, the higher the

prob-ability associated with χ2, the closer the fit between the

hypothesized model (under H0) and the perfect fit [31]

As of our probability of 0.11 reveals (p > 0.05,

non-significant), our model can be defined as a well-fitted

model

We used the CMIN/DF value as a second measure to

test the fit of our model Values of CMIN/DF lower than

2 indicate an acceptable fit [32-34], and our model

ful-filled this criterion (CMIN/DF = 1.117)

The NFI value was 906, and the CFI value was 989 as

shown in Table 3 The NFI value suggested that the

model fit was only marginally adequate (NFI: 906), yet

acceptable, but the CFI value suggests a superior fit

(CFI: 989) The Incremental Index of Fit (IFI) [35] was

developed to address issues of parsimony and sample

size, which are known to be associated with the NFI

Unsurprisingly, our IFI of 989 is more consistent with

the CFI and reflects a well-fitting model Finally, the Tucker-Lewis Index (TLI) [36], consistent with the other indices noted here, yielded values ranging from zero to 1.00, with values close to 95 (for large samples) being indicative of good fit [37] As shown in Table 3, our TLI value of 986 is indicative of a superior fit of our model The final index was the Root Mean Square Error of Approximation (RMSEA) This index was one of the most informative criteria in covariance structure modeling The RMSEA takes into account the error of approximation in the population and asks the question “How well would the model, with unknown but optimally chosen parameter values, fit the population covariance matrix if it were avail-able?” [38] This discrepancy, as measured by the RMSEA,

is expressed per degree of freedom, thus making it sensi-tive to the number of estimated parameters in the model (i.e., the complexity of the model); values less than 05 in-dicate good fit The RMSEA value in our model was 019

as shown in Table 3, which represents a good fit

When all of the indices are considered, we conclude that the proposed model fits our data well The child’s perception of acceptance/rejection by the mothers sig-nificantly predicts aggression at home (β = 21, p = 012), whereas this perception does not predict aggression at school (p = 238) Family factors significantly predict ag-gression at home (β = 68, p < 001), and agag-gression at

Measurement (CFA) Model

Structural Model Figure 1 Structural equation modeling of aggression in elementary school students with ADHD (standardized solution; N = 476;

*: p < 0.05, **: p < 0.001).

school (β = 44, p < 001) Likewise, cognitive factors

sig-nificantly predict aggression at home (β = −.12, p = 032)

and aggression at school (β = −.05, p = 028)

When all predictors of aggression levels are considered

together, they predict 52% of the variance in overall

aggression at home and 20% of the overall variance in

aggression at school

Discussion

Even though aggressive behavior in children with ADHD

is highly prevalent, it is not well understood [3] Despite

the existing literature on the influence of family factors,

cognitive function and parent–child relationship

pro-blems on aggression in ADHD, there are few studies

concerning the relationships of these factors with ag-gression at home and school To the best of our know-ledge, this is the first study examining the influence of family, cognitive and maternal acceptance or rejection factors on school-age children with ADHD with a large sample and using structural equation modeling

The most important finding from this study is that family is the most important factor in predicting aggres-sion in children with ADHD both at school and at home This finding is in accordance with the findings of Miller et al [16], which also model factors relating to aggression in ADHD with similar methodologies and statistics [16] In both studies, family factors are found

to be the most important factors in aggression both at

Table 3 Unstandardized estimates, standardized estimates, determination coefficients, and significance levels for model in Figure 1 (N = 476)

Structural model

χ 2

(223) = 249.199, p = 0.11, CMIN/DF = 1.117, NFI = 0.906, CFI = 0.989, IFI = 0.989, TLI = 0.986, RMSEA = 0.019.

school and at home In our study, parents’ past and

present aggression, the number of siblings and the

num-ber of people living in the same home are also evaluated

as potential family indicators We find that the number of

siblings and the number of people living in the home do

not significantly predict aggression at school or at home

Parents’ past and present aggression is the most important

variable for predicting the aggression of children at school

and at home This finding is consistent with previous

research, which clearly suggests that parents’ antisocial

be-havior is strongly and specifically related to their children’s

aggressive behavior [39] Although it is difficult to parse

out the genetic and environmental influences, it is likely

that aggressive parents play an important role in the emer-gence and persistence of aggression in children For ex-ample, one study indicates that the more the aggressive parent is absent from the home, the smaller the effect that parent’s behavior has on the behavior of the children in the home [40] Even if the genetic contribution of parents’ aggressive behavior is controlled, parental aggression nonetheless affects the child’s aggressive behaviors [41] These findings in these studies support the importance of modeling environmental effects

In our study, we evaluated the perceptions of children with ADHD regarding their acceptance or rejection by their mothers The child’s perception of acceptance of

Table 4 Comparison of factor loading unstandardized parameter estimates: maximum likelihood versus Bayesian estimation

Estimation approach

Structural model

rejection by the mothers is only related to aggression at

home and not to aggression at school In addition, we

found that family factors predict aggression at home

more than acceptance or rejection by the mother

This finding suggests that the relationship between

parenting and children’s behavior may be more

compli-cated than previously thought, though it is in accordance

with other studies of the influence of maternal attitudes

on childhood aggression In contrast with these previous

studies, recent studies show that the correlation between

parenting and children’s behavioral problems may not be

linear Yeh, Chen, Raine, Bakre, & Jacobson [42] find

that the correlation between parenting and children’s

behavioral problems depends upon the intensity of the

children’s behavioral problems In other words, similar

parental attitudes may have different influences on

dif-ferent children Cartwright et al [43] also found that

negative maternal emotions expressed towards children

with ADHD (e.g., low warmth and hostility/criticism)

are more damaging than emotions expressed towards

children without ADHD In this case, in addition to the impact of negative parenting on behavioral problems in children, it is important to also consider the influence of children’s behavioral problems on parents’ attitudes In the study of Lifford et al [44] a casual hypothesis of family relations influencing ADHD symptoms was not supported Moreover, in many studies evaluating paren-tal attitudes towards ADHD, parenparen-tal attitudes improve after the administration of methylphenidate for the ment of their children’s ADHD [45] As a result of treat-ment, the resulting amelioration of the behavior may change the mother’s attitude towards the child Based on these findings, the fact that maternal acceptance or rejection predicts childhood aggression only at home and is less predictive than other family factors suggests that parent–child relations have a secondary influence in cases of ADHD and that past and current parental ag-gression are the most important factors

The third aim of our study was to evaluate the effects

of cognitive factors on aggression in children with

0,81

Figure 2 Structural equation modeling of aggression in elementary school students with ADHD (standardized solution; N = 476;

*: p < 0.05, **: p < 0.001).

ADHD Our findings reveal that children with lower

cognitive function show more aggressive behaviors both

at school and at home This finding is consistent with

many other studies in the literature, which also report

that aggressive children have problems in social

cog-nitive areas [10,11] and have lower IQ scores [12-14]

However, in our study, the correlation between cognitive

factors and aggression at school and at home is less

in-fluential than family factors This new information

sug-gests that cognitive factors may have a limited scope of

influence

Limitations

The most important limitation of this study is its

cross-sectional methodology Longitudinal studies are needed

to better assess aggression in cases of ADHD In

ad-dition, this study was not able to evaluate whether

ag-gression is relational or social The fact that the family’s

socioeconomic situation was not assessed in detail is

an-other limitation of our study Anan-other limitation of our

study is that maternal acceptance and rejection

percep-tions were assessed, but paternal acceptance and

rejec-tion perceprejec-tions were not assessed

Clinical implications

ADHD is a prevalent psychiatric disorder, and it may

cause significant complications if left untreated The

co-morbidity of aggression has a negative influence on the

treatment and prognosis of ADHD In cases of ADHD

co-morbid with aggression, aggressive symptoms are more

apparent and continuous compared to ADHD cases

with-out aggression Within this context, it is appropriate to

evaluate ADHD cases first in terms of family factors, and

then for cognitive and parent–child relational factors

before the emergence of aggressive symptoms

Key points

 What’s known: Past research has shown that when a

child is referred with aggressive symptoms, one of

the most common diagnoses is attention-deficit

hyperactivity disorder (ADHD)

 What’s new: Previous studies have not examined

which demographic factors, family factors,

perception of acceptance/rejection by the mothers

and cognitive factors differentially correlate with

aggression at home and at school

 Findings: Family factors, cognitive factors and

perception of acceptance/rejection by the mothers

are important aspects of ADHD children’s

aggression

 This study confirms that family factors affect

aggressive behaviors of ADHD children at home and

at school settings

 Cognitive factors determine the aggressive behaviors

of elementary school students’ aggression in both school and home

 The child’s perception of acceptance of rejection by the mothers is related to aggression at home and not to aggression at school

 Implications: Prevention and intervention programs that target aggressive behaviors of ADHD children

by focusing on family factors, cognitive factors and perception of acceptance rejection by parents may have the most impact

Competing interest The study was not supported by any financial funding No financial or material support was taken for the study Dr Ercan is on advisory boards for Eli Lilly Turkey and Janssen Turkey The other authors have no biomedical financial interests or potential conflicts of interest.

Authors ’ contributions All authors but BKB contributed equally to the design and conduct of the study, interpretation of the results, and writing of the manuscript BKB was responsible for collection of the data All authors read and approved the final manuscript.

Acknowledgements

We are grateful to (in alphabetical order) Ayse Er, Gunay Sagduyu and Semra Ucar for administration and scoring of the WISC-R We are also thankful to children, parents and teachers who took part in this study.

Author details 1

Department of Psychological Counseling and Guidance, Ege University Faculty of Education, Izmir, Turkey 2 Department of Child and Adolescent Psychiatry, Ege University Faculty of Medicine, Izmir, Turkey 3 Department of Educational Sciences Measurement and Evaluation in Education, Ege University Faculty of Education, Izmir, Turkey.4Ege University Institute on Drug Abuse, Toxicology and Pharmaceutical Science, İzmir, Turkey 5 Child and Adolescent Psychiatry, Denizli, Turkey.

Received: 10 October 2013 Accepted: 12 May 2014 Published: 15 May 2014

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doi:10.1186/1753-2000-8-15 Cite this article as: Ercan et al.: Predicting aggression in children with ADHD Child and Adolescent Psychiatry and Mental Health 2014 8:15.

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